Epithelial ovarian cancer has become the most frequent cause of deaths among gynecologic malignancies. Our study elucidates the diagnostic performance of Risk of Ovarian Malignancy Algorithm (ROMA), Human epididymis secretory protein 4 (HE4) and cancer antigen (CA125). To compare the diagnostic accuracy of ROMA, HE-4 and CA125 in the early diagnosis and screening of Epithelial Ovarian Cancer. Literature search in electronic databases such as Medicine: MEDLINE (through PUBMED interface), EMBASE, Google Scholar, Science Direct and Cochrane library from January 2011 to August 2020. Studies that evaluated the diagnostic measures of ROMA, HE4 and CA125 by using Chemilumincence immunoassay or electrochemiluminescence immunoassay (CLIA or ECLIA) as index tests. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). We included 32 studies in our meta-analysis. We calculated AUC by SROC, pooled estimated like sensitivity, specificity, likelihood ratio, diagnostic odds ratio (DOR), Tau square, Cochran Q through random effect analysis and meta-regression. Data was retrieved from 32 studies. The number of studies included for HE4, CA125 and ROMA tests was 25, 26 and 22 respectively. The patients with EOC were taken as cases, and women with benign ovarian mass were taken as control, which was 2233/5682, 2315/5875 and 2281/5068 respectively for the markers or algorithm. The pooled estimates of the markers or algorithm were sensitivity: ROMA (postmenopausal) (0.88, 95% CI 0.86–0.89) > ROMA (premenopausal) 0.80, 95% CI 0.78–0.83 > CA-125(0.84, 95% CI 0.82–0.85) > HE4 (0.73, 95% CI 0.71–0.75) specificity: HE4 (0.90, 95% CI 0.89–0.91) > ROMA (postmenopausal) (0.83, 95% CI 0.81–0.84) > ROMA (premenopausal) (0.80, 95% CI 0.79–0.82) > CA125 (0.73, 95%CI 0.72–0.74), Diagnostic odd’s ratio ROMA (postmenopausal) 44.04, 95% CI 31.27–62.03, ROMA (premenopausal)-18.93, 95% CI 13.04–27.48, CA-125-13.44, 95% CI 9.97–18.13, HE4-41.03, 95% CI 27.96–60.21 AUC(SE): ROMA (postmenopausal) 0.94(0.01), ROMA (premenopausal)-0.88(0.01), HE4 0.91(0.01), CA125-0.86(0.02) through bivariate random effects model considering the heterogeneity. Our study found ROMA as the best marker to differentiate EOC from benign ovarian masses with greater diagnostic accuracy as compared to HE4 and CA125 in postmenopausal women. In premenopausal women, HE4 is a promising predictor of Epithelial ovarian cancer; however, its utilisation requires further exploration. Our study elucidates the diagnostic performance of ROMA, HE4 and CA125 in EOC. ROMA is a promising diagnostic marker of Epithelial ovarian cancers in postmenopausal women, while HE4 is the best diagnostic predictor of EOC in the premenopausal group. Our study had only EOC patients as cases and those with benign ovarian masses as controls. Further, we considered the studies estimated using the markers by the same index test: CLIA or ECLIA. The good number of studies with strict inclusion criteria reduced bias because of the pooling of studies with different analytical methods, especially for HE4. We did not consider the studies published in foreign languages. Since a few studies were available for HE4 and CA125 in the premenopausal and postmenopausal group separately, data were inadequate for sub-group analysis. Further, we did not assess these markers' diagnostic efficiency stratified by the stage and type of tumour due to insufficient studies.

Results:We found significantly high levels of sd LDL, ox LDL, Apo B, Lp (a), TC, TG, LDL-C in cases as compared to the controls. Ox LDL has shown maximum correlation with serum TSH (p<0.0001, r=0.801) followed by sd LDL (p<0.0001, r=0.792), Apo B (p<0.001, r=0.783) and LDL-C (p<0.001, r=0.741). Moreover, ox LDL and sd LDL were found to be increased in normolipidemic hypothyroid patients thereby giving a strong supportive evidence that estimation of these parameters can become fundamental in prompt identification of the high risk patients of CAD in hypothyroid population. Conclusion:Non-conventional lipid parameters appear to be better markers for the assessment of cardiovascular risk in hypothyroidism and might help in the designing of the effective treatment protocols and areas of intervention by the clinicians as well as researchers.

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Introduction:The high prevalence, severity, and prematurity of coronary artery disease (CAD) in the Indian population cannot be completely explained by the conventional lipid parameters and the existing lipid indices.Aims and Objectives:To calculate newly defined advanced atherogenic index (AAI) in premature CAD patients and compare it between cases and controls and Correlate its values with the existing indices.Material and Methods:One hundred and twenty premature CAD patients and an equal number of age and sex matched healthy individuals were included in this study. Lipid profile and nonconventional lipid parameters like oxidized Low density lipoprotein (OX LDL), small dense LDL (SD LDL), lipoprotein (a) apolipoprotein B (Apo B), and apolipoprotein A1 (Apo A1) were estimated and their values were used to define AAI and existing lipid indices like AI, lipid tetrad index (LTI) and lipid pentad index (LPI).Results:The mean age of cases and controls was 37.29 + 4.50 and 36.13 + 3.53 years, respectively. The value of AAI was highly significant in cases (3461.22 ± 45.20) as compared to controls (305.84 ± 21.80). AAI has shown better statistical significance and correlation (P < 0.0001, r = 0.737) as compared to the earlier indices such as AI (P < 0.01, r = 0.52), LTI (P < 0.001, r = 0.677) and LPI (P < 0.001, r = 0.622) in premature CAD. Kolmogorov D statistic and cumulative distribution function plot has shown that AAI can discriminate cases and controls more accurately as compared to the earlier indices.Conclusion:Statistically AAI appears to be a better marker of consolidated lipid risk in premature CAD patients as compared to the earlier indices.